4 of 4 Permanent Apache Spark Jobs in Wakefield

project management tools (JIRA or similar) in an agile environment. Familiarity with other ML Ops tools (Kubeflow, MLflow, etc.) or big data processing frameworks (Spark) can be an added advantage Rewards and Benefits We believe in supporting our employees in both their professional and personal lives. As part

Data Engineering, with a minimum of 3 years of hands-on Azure Databricks experience delivering production-grade solutions. Strong programming proficiency in Python and Spark (PySpark) or Scala, with the ability to build scalable and efficient data processing applications. Advanced understanding of data warehousing concepts, including dimensional modelling

/test workloads are self-orchestrated using clustered Proxmox as a private cloud. Our analytics workloads are distributed on bare metal using Spark, HBASE and HDFS. We make extensive use of terraform and ansible for IaC, our CI/CD uses GitHub Actions, our observability is provided via Datadog

production at scale. Technical Skills: Strong backend Python; expertise with ML frameworks (TensorFlow, PyTorch, Scikit-Learn, etc.); familiarity with modern data pipeline tools (Airflow, Spark, Kafka) and workflow orchestration frameworks such as n8n or LangGraph. Applied AI: Background in enterprise applications such as chatbots, workflow automation, RAG pipelines